Adaptive fusion of K-means region growing with optimized deep features for enhanced LSTM-based multi-disease classification of plant leaves-Reference-Cited by-同舟云学术

Adaptive fusion of K-means region growing with optimized deep features for enhanced LSTM-based multi-disease classification of plant leaves

Published:2023-05-15 Issue:1 Volume:38 Page:
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Sahu Kalicharan¹,Minz Sonajharia¹

Affiliation:

1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2023.2178520

Reference53 articles.

1. A 3D CNN-LSTM-Based Image-to-Image Foreground Segmentation

2. Plant leaf disease classification using EfficientNet deep learning model

3. Region Growing for Segmenting Green Microalgae Images

4. Brammya G, Praveena S, Preetha NSN, Ramya R, Rajakumar BR, Binu D. 2019. Deer hunting optimization algorithm: a new nature-inspired meta-heuristic paradigm. The Computer Journal.

5. Chouhan SS Kaul A Singh UP Jain S. 2018. Bacterial Foraging Optimization Based Radial Basis Function Neural Network (BRBFNN) for identification and classification of plant leaf diseases: An automatic approach towards plant pathology Institute of Electrical and Electronics Engineers Access 6 8852–8863.

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